Coordinating analytics methods for mobile healthcare applications

Chowdhary, Pawan; Lee, Sunhwan; Timm, John T. E.; Ludwig, Heiko; Knoop, Sarah

doi:10.1145/2897683.2926711

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…Ong et al [14] conducted a study that integrates smart phones as a self-management tool for patients in an outpatient clinic, and concluded that it is feasible and acceptable; similar study can be found in [15]. Chowdhary et al [16] proposed a software architecture framework that can simplify using analytics in the mobile-healthcare applications.…”

Section: Literature Reviewmentioning

confidence: 87%

Towards Patient-oriented Design: A Case of the Egyptian Private Outpatient Clinics

Heshmat¹,

Mostafa²,

Park³

2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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Section: Literature Reviewmentioning

confidence: 87%

Towards Patient-oriented Design: A Case of the Egyptian Private Outpatient Clinics

Heshmat¹,

Mostafa²,

Park³

2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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“…They seem to reach similar conclusions to ours and complement them with additional remarks. For example, [25] proposes a framework for supporting analytics in mobile health applications while [26] describes the functionality and architecture of both the frontend app and the backend system for a smartphone e-health app that supports maternal health workers in rural India. The work in [27] illustrates instead the development of three concrete app examples natively on the cloud using Apache OpenWhisk [28].…”

Section: Related Literature and Conclusionmentioning

confidence: 99%

Wandering and getting lost: the architecture of an app activating local communities on dementia issues

Andersen

Chiarandini

Mauro

2021

2021 IEEE/ACM 3rd International Workshop on Software Engineering for Healthcare (SEH)

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We describe the architecture of Sammen Om Demens (SOD), an application for portable devices aiming at helping persons with dementia when wandering and getting lost through the involvement of caregivers, family members, and ordinary citizens who volunteer.To enable the real-time detection of a person with dementia that has lost orientation, we transfer location data at high frequency from a frontend on the smartphone of a person with dementia to a backend system. The backend system must be able to cope with the high throughput data and carry out possibly heavy computations for the detection of anomalous behavior via artificial intelligence techniques. This sets certain performance and architectural requirements on the design of the backend.In the paper, we discuss our design and implementation choices for the backend of SOD that involve microservices and serverless services to achieve efficiency and scalability. We give evidence of the achieved goals by deploying the SOD backend on a public cloud and measuring the performance on simulated load tests.

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“…There is growing recognition for Mobile healthcare application with great increase in the availability of sensors in mobile devices. The analytical framework for Mobile health care applications has been discussed [10] along with a case study on the implementation details. Such high volumes of data collected through big data techniques could have huge impacts on the health care industry and the predictive models built through them.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Big Data Analytics Based Framework for Premature Recognition of Breast Cancer

Venkatesan*,

Kulkarni,

Menon

et al. 2020

IJITEE

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Healthcare industry is fast growing and expanding in rapid pace. The volume and veracity of data generated in the industry is massive and requires huge storages and handling capability. Big data is empowered with such robust abilities and hence most suitable for handing large amount of data. Further, hese data could be utilized towards building predictive and forecasting models. Breast cancer is a deadly form of cancer majorly affecting women around the globe. The concept of big data and predictive analytics is being explored in the paper towards early diagnosis of breast cancer. This paper surveys various literatures available on application of big data analysis for breast cancer. Subsequently a comprehensive framework is being proposed based on the gaps identified. Different machine learning algorithms which can be applied in the framework is also detailed in the paper. Such frameworks when implemented will greatly help in handling the massive data available and aid in early detection of breast cancer.

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Coordinating analytics methods for mobile healthcare applications

Cited by 3 publications

References 4 publications

Towards Patient-oriented Design: A Case of the Egyptian Private Outpatient Clinics

Towards Patient-oriented Design: A Case of the Egyptian Private Outpatient Clinics

Wandering and getting lost: the architecture of an app activating local communities on dementia issues

A Comprehensive Big Data Analytics Based Framework for Premature Recognition of Breast Cancer

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